Phyloclimatic modeling: Combining phylogenetics and bioclimatic modeling

We investigate the impact of past climates on plant diversification by tracking the "footprint" of climate change on a phylogenetic tree. Diversity within the cosmopolitan carnivorous plant genus Drosera (Droseraceae) is focused within Mediterranean climate regions. We explore whether this diversity is temporally linked to Mediterranean-type climatic shifts of the mid-Miocene and whether climate preferences are conservative over phylogenetic timescales. Phyloclimatic modeling combines environmental niche (bioclimatic) modeling with phylogenetics in order to study evolutionary patterns in relation to climate change. We present the largest and most complete such example to date using Drosera. The bioclimatic models of extant species demonstrate clear phylogenetic patterns; this is particularly evident for the tuberous sundews from southwestern Australia (subgenus Ergaleium). We employ a method for establishing confidence intervals of node ages on a phylogeny using replicates from a Bayesian phylogenetic analysis. This chronogram shows that many clades, including subgenus Ergaleium and section Bryastrum, diversified during the establishment of the Mediterranean-type climate. Ancestral reconstructions of bioclimatic models demonstrate a pattern of preference for this climate type within these groups. Ancestral bioclimatic models are projected into palaeo-climate reconstructions for the time periods indicated by the chronogram. We present two such examples that each generate plausible estimates of ancestral lineage distribution, which are similar to their current distributions. This is the first study to attempt bioclimatic projections on evolutionary time scales. The sundews appear to have diversified in response to local climate development. Some groups are specialized for Mediterranean climates, others show wide-ranging generalism. This demonstrates that Phyloclimatic modeling could be repeated for other plant groups and is fundamental to the understanding of evolutionary responses to climate change.

Combining competition from Lolium perenne and an insect-fungus combination to control Rumex obtusifolius seedlings

Although adult Rumex obtusifolius are problematic weeds, their seedlings are poor competitors against Lolium perenne, particularly in established swards. We investigated the possibility of using this weakness to augment control of R. obtusifolius seedlings with combinations of Gastrophysa viridula (Coleoptera: Chrysomelidae) and the rust fungus Uromyces rumicis. Rumex obtusifolius seedlings were grown in competition with L. perenne sown at different rates and times after R. obtusifolius: they competed successfully with L. perenne when sown 21 days before the grass. Sowing both species at the same time resulted in a dominant grass sward, with R. obtusifolius becoming dominant when sown 42 days prior to L. perenne. Grass sowing rate had no effect on R. obtusifolius growth or biomass. A second experiment investigated how competition from L. perenne sown 21 days after R. obtusifolius combined with damage from G. viridula and/or U. rumicis (applied at either the 3-4- or 10-13-leaf stage, or at both stages) affected the growth and final biomass of R. obtusifolius. Beetle grazing at the latter leaf stage was the only treatment that reduced R. obtusifolius biomass, although rust infection at the earlier application led to an increase in shoot and root weight. The results are discussed in terms of the potential for use of these agents in the field.

Analysis of the antigen combining site: Correlations between length and sequence composition of the hypervariable loops and the nature of the antigen

It has long been suggested that the overall shape of the antigen combining site (ACS) of antibodies is correlated with the nature of the antigen. For example, deep pockets are characteristic of antibodies that bind haptens, grooves indicate peptide binders, while antibodies that bind to proteins have relatively flat combining sites. In. 1996, MacCallum, Martin and Thornton used a fractal shape descriptor and showed a strong correlation of the shape of the binding region with the general nature of the antigen. However, the shape of the ACS is determined primarily by the lengths of the six complementarity-determining regions (CDRs). Here, we make a direct correlation between the lengths of the CDRs and the nature of the antigen. In addition, we show significant differences in the residue composition of the CDRs of antibodies that bind to different antigen classes. As well as helping us to understand the process of antigen recognition, autoimmune disease and cross-reactivity these results are of direct application in the design of antibody phage libraries and modification of affinity. (C) 2003 Elsevier Science Ltd. All rights reserved.

Combining physical, cultural and biological methods: prospects for integrated non-chemical weed management strategies

Physical, cultural and biological methods for weed control have developed largely independently and are often concerned with weed control in different systems: physical and cultural control in annual crops and biocontrol in extensive grasslands. We discuss the strengths and limitations of four physical and cultural methods for weed control: mechanical, thermal, cutting, and intercropping, and the advantages and disadvantages of combining biological control with them. These physical and cultural control methods may increase soil nitrogen levels and alter microclimate at soil level; this may be of benefit to biocontrol agents, although physical disturbance to the soil and plant damage may be detrimental. Some weeds escape control by these methods; we suggest that these weeds may be controlled by biocontrol agents. It will be easiest to combine biological control with. re and cutting in grasslands; within arable systems it would be most promising to combine biological control (especially using seed predators and foliar pathogens) with cover-cropping, and mechanical weeding combined with foliar bacterial and possibly foliar fungal pathogens. We stress the need to consider the timing of application of combined control methods in order to cause least damage to the biocontrol agent, along with maximum damage to the weed and to consider the wider implications of these different weed control methods.

Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo

This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

Hitting emissions targets with (statistical) confidence in multi-instrument Emissions Trading Schemes

A means of assessing, monitoring and controlling aggregate emissions from multi-instrument Emissions Trading Schemes is proposed. The approach allows contributions from different instruments with different forms of emissions targets to be integrated. Where Emissions Trading Schemes are helping meet specific national targets, the approach allows the entry requirements of new participants to be calculated and set at a level that will achieve these targets. The approach is multi-levelled, and may be extended downwards to support pooling of participants within instruments, or upwards to embed Emissions Trading Schemes within a wider suite of policies and measures with hard and soft targets. Aggregate emissions from each instrument are treated stochastically. Emissions from the scheme as a whole are then the joint probability distribution formed by integrating the emissions from its instruments. Because a Bayesian approach is adopted, qualitative and semi-qualitative data from expert opinion can be used where quantitative data is not currently available, or is incomplete. This approach helps government retain sufficient control over emissions trading scheme targets to allow them to meet their emissions reduction obligations, while minimising the need for retrospectively adjusting existing participants’ conditions of entry. This maintains participant confidence, while providing the necessary policy levers for good governance.

Planning the sustainable eco-city in Taipei: The implementation of green design and green building schemes

Taipei City has put a significant effort toward the implementation of green design and green building schemes towards a sustainable eco-city. Although some of the environmental indicators have not indicated significant progress in environmental improvement, implementing the two schemes has obtained considerable results; therefore, the two schemes are on the right path towards promoting a sustainable eco-city. However, it has to be admitted that the two schemes are a rather “technocratic” set of solutions and eco-centric approach. It is suggested that not only the public sector but also the private sector need to put more effort toward implement the schemes, and the government needs to encourage the private sector to adopt the schemes in practice.

Combining Human and Machine Brains - Practical systems in information & control

In this paper a look is taken at how the use of implant technology can be used to either increase the range of the abilities of a human and/or diminish the effects of a neural illness, such as Parkinson's Disease. The key element is the need for a clear interface linking the human brain directly with a computer. The area of interest here is the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Pilot tests and experimentation are invariably carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed here. The paper goes on to describe human experimentation, in particular that carried out by the author himself, which led to him receiving a neural implant which linked his nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them. In particular, feedback to the brain was obtained from the fingertips of a robot hand and ultrasonic (extra) sensory input. A view is taken as to the prospects for the future, both in the near term as a therapeutic device and in the long term as a form of enhancement.

Computational complexity of weighted splitting schemes on parallel computers

In models of complicated physical-chemical processes operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The recently rediscovered weighted splitting schemes have the great advantage of being parallelizable on operator level, which allows us to reduce the computational time if parallel computers are used. In this paper, the computational times needed for the weighted splitting methods are studied in comparison with the sequential (S) splitting and the Marchuk-Strang (MSt) splitting and are illustrated by numerical experiments performed by use of simplified versions of the Danish Eulerian model (DEM).